Fault Tree Analysis of Pantograph Type Current Collector Based on Ontology Modeling

Long Long Song; Wang Tai Yong; Lei Xu; Xiao Wen Song

doi:10.4028/www.scientific.net/KEM.693.1371

Paper Titles

Binary Resolution Matrix Based Incremental Attribute Reduction for Fault Diagnosis
p.1346

Blind Source Separation for Under-Determined Mixtures Based on Time-Frequency Analysis
p.1350

Composite Fault Diagnosis and Intelligent Maintenance Based on Data Driven
p.1357

Fault Feature Extraction Method of the Rolling Element Bearing Based on Reverse Order Tracking
p.1361

Fault Tree Analysis of Pantograph Type Current Collector Based on Ontology Modeling
p.1371

One Abstraction Method for Displacement Response in the Sweep-Frequency Testing of Rotating Spindle
p.1377

Petri Nets in the Emu Pantograph Application of Fault Tree Analysis (FTA)
p.1385

Research and Simulation of SVPWM Algorithm Based on BP Neural Network
p.1391

Research of Multi-Sensor Data Fusion Based on Binocular Vision Sensor and Laser Range Sensor
p.1397

HomeKey Engineering MaterialsKey Engineering Materials Vol. 693Fault Tree Analysis of Pantograph Type Current...

Fault Tree Analysis of Pantograph Type Current Collector Based on Ontology Modeling

Abstract:

Complex mass faults diagnosis of the pantograph type current collector was difficult. Based on the analysis of the structure, working principle and failure mode of the pantograph type current collector, fault tree of the pantograph was established. A lot of expert knowledge has been collected to support this diagnose process. Some serious problems such as ambiguity, uncertainty and inconsistency exist in the knowledge. Focused on the deficiencies, ontology modeling was proposed in this paper. StrOnto, FaultOnto and FTOnto were established to standardize the knowledge and to improve the efficiency of fault diagnosing. Finally, combined with the example of the pantograph type current collector of CRH2 EMU-train, the proposed algorithms proposed in this paper were proved reasonable and effective.

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Periodical:

Key Engineering Materials (Volume 693)

Pages:

1371-1376

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.693.1371

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Online since:

May 2016

Authors:

Long Long Song*, Wang Tai Yong, Lei Xu, Xiao Wen Song

Keywords:

Fault Diagnosis, Fault Tree Analysis, Knowledge Sharing, Ontology Modeling, Pantograph Type Current Collector

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